Tensorflow, developed by Google, has become the most popular framework for deep learning, and now operates on a variety of devices including multicore CPUs, general purpose GPUs, mobile devices, and custom ASICs.
In this on-demand webinar hosted by Intel and ActiveState, you’ll get a general introduction to working with Tensorflow and its surrounding ecosystem, general problem classes, where you can get big acceleration, and why you should be running on a CPU.
- Ideal use cases for TensorFlow on CPUs, including which models and types of operations benefit the most
- Proposed benchmarks, projected accelerations, and how to tune performance for your systems
- Advanced topics like using multiple nodes to train on large __data science packages included with ActivePython can help accelerate your algorithms
Mohammad Ashraf Bhuiyan, Intel Artificial Intelligence Group, Senior Software Engineer
Pete Garcin, Developer Advocate, ActiveState